Project Description

.. raw:: html

<p align="center"> <img src="logo.png"> </p>

|Hex.pm| |Build.pm|

Studio is a model management framework written in Python to help simplify and expedite your model building experience. It was developed to minimize the overhead involved with scheduling, running, monitoring and managing artifacts of your machine learning experiments. No one wants to spend their time configuring different machines, setting up dependencies, or playing archeologist to track down previous model artifacts.

Most of the features are compatible with any Python machine learningframework (`Keras <https://github.com/fchollet/keras>`__,`TensorFlow <https://github.com/tensorflow/tensorflow>`__,`PyTorch <https://github.com/pytorch/pytorch>`__,`scikit-learn <https://github.com/scikit-learn/scikit-learn>`__, etc);some extra features are available for Keras and TensorFlow.

You can see results of your job at http://127.0.0.1:5000. Run``studio {ui|run} --help`` for a full list of ui / runner options

Installation------------

pip install studioml from the master pypi repositry:

::

pip install studioml

Find more `details <docs/installation.rst>`__ on installation methods and the release process.

Authentication--------------

Currently Studio supports 2 methods of authentication: `email / password <docs/authentication.rst#email--password-authentication>`__ and using a `Google account. <docs/authentication.rst#google-account-authentication>`__ To use studio runner and studio ui in guestmode, in studio/default\_config.yaml, uncomment "guest: true" under thedatabase section.

Alternatively, you can set up your own database and configure Studio touse it. See `setting up database <docs/setup_database.rst>`__. This is apreferred option if you want to keep your models and artifacts private.